"Using Claude Desktop and Code MCP to manage Google Cloud Platform/Vertex AI projects" matching MCP servers:

Bridges Claude Desktop with Claude Code CLI to delegate complex coding tasks like creating React apps, building APIs, and debugging scripts while maintaining interaction through the Desktop interface.

An MCP server that implements Claude Code-like functionality, allowing the AI to analyze codebases, modify files, execute commands, and manage projects through direct file system interactions.

An MCP server that gives orchestrator agents fine-grained control over interactive Claude Code sessions running inside tmux, enabling mid-session steering, interruption, and token-efficient result extraction.

An implementation of Claude Code as a Model Context Protocol server that enables using Claude's software engineering capabilities (code generation, editing, reviewing, and file operations) through the standardized MCP interface.

This project aims to build a Claude Code MCP server and implement its associated tools (explain\_code, review\_code, fix\_code, edit\_code, test\_code, simulate\_command, your\_own\_query). The server is implemented using Node.js and the MCP SDK. It receives tool requests from clients via Stdio, dynamically

An MCP server that allows Claude Desktop to remotely control Claude Code instances for executing commands and managing files.

A runtime-free MCP server that converts source code into AST🌲, regardless of language.

This MCP server exposes Claude Code as a tool, allowing MCP clients to run Claude Code agents in specified working directories. It manages session persistence and returns structured results including summary, changed files, tests, and blockers.

A server that allows LLMs to run Claude Code with all permissions bypassed automatically, enabling code execution and file editing without permission interruptions.

An enhanced Model Context Protocol (MCP) server that allows running Claude Code in one-shot mode with permissions bypassed automatically, featuring advanced task

Enables Claude Code to delegate tasks to OpenAI's Codex CLI (GPT-5.4) with structured execution traces, parallel execution, session persistence, and adversarial code review.

Bridges Claude Desktop, Claude Code CLI, and Claude Code for VS Code, enabling developers to plan in Desktop, save specs to project directories, and invoke Claude Code CLI with seamless state sharing across interfaces.

A Model Context Protocol (MCP) server that provides comprehensive Jupyter notebook interaction capabilities, compatible with Claude Code.

Enables Codex to delegate tasks to Claude Code, allowing Claude to investigate, edit, and verify changes in the repository with background job management.

Wraps Claude Code as a server using the Model Context Protocol (MCP), allowing teams to interact with Claude Code through a Slack bot interface.

Exposes Claude Code's file editing, command execution, and test running capabilities as composable MCP tools for any MCP-compatible host, enabling code operations via a stateless bridge.

Enables ISLI agents and MCP clients to dispatch natural-language coding and terminal tasks to a locally-installed Claude Code CLI, supporting both one-shot execution and persistent sessions with workspace and security controls.

Allows Claude to execute terminal commands on your computer and perform file system operations including surgical code editing with diff-based replacements.

An MCP server that provides code review functionality using OpenAI, Google, and Anthropic models, serving as a "second opinion" tool that works with any MCP client.

Enables Claude to control Unity Hub and Editor headlessly, allowing automated game building, asset generation, and PBR texture creation.

The Problem Modern distributed systems and AI agents require robust operational scaffolding. Simple CRUD apps or mock loops fail when subjected to real-world edge cases, asynchronous boundaries, and security constraints. The Solution An isolated execution platform for AI agents. An agent is given a broken service and a bounded toolset inside a disposable sandbox. Every command passes throug

A code-first MCP server that provides a single tool to execute JavaScript or TypeScript with authenticated access to Google Workspace APIs. It enables flexible interactions with services like Calendar and Drive by running user-provided scripts through a built-in runtime environment.

Enables AI agents to search, update, manage files, and run terminal commands on a computer, with remote access via Streamable HTTP and OAuth 2.0 for integration with ChatGPT and web agents.

Enables AI coding agents to generate standardized code using scaffolding templates, enforce architectural patterns, and validate outputs programmatically. Supports creating projects from boilerplates and adding features to existing codebases while maintaining team conventions.

MCP server that routes medical questions and images to MedGemma models hosted on Vertex AI, enabling interaction with text-only and multimodal medical AI systems.

An MCP server that bridges Claude Desktop with Claude Code, allowing users to delegate tasks to Claude Code directly from Claude Desktop conversations, supporting both synchronous and background execution with session reuse.

Enables Claude Code to execute shell commands, Python code, and file transfers on a Google Colab T4 GPU via an MCP server, bridging the GPU gap for AI coding agents.

A cross-platform desktop MCP server that allows Codex and other MCP clients to execute tasks via the Claude Agent SDK, providing tools for code generation, file editing, and task management with session continuation.

MCP server for the Agent Platform API, enabling management of sandbox environments through MCP protocol. Exposes tools to interact with sandbox lifecycle operations such as start, stop, and status checks.

Enables AI agents to run untrusted, model-generated Python code in a locked-down throwaway Docker container with enforced isolation and resource limits. Supports starting, checking, and stopping asynchronous runs while returning structured status reports without exposing the host, network, or Docker controls.